Considering user-relevant criteria when serving advertisements

ABSTRACT

The present invention is directed to selecting an advertisement to be presented in an ad space of a webpage. A criterion (e.g., keyword, image, audio element, etc.) is selected to evoke the advertisement. In an embodiment, the criterion is selected based on a relevance of the criteria to a user, and not necessarily based solely on a relevance to the webpage. Whether a criterion should be used to evoke the advertisement might be based on various factors, such as the likelihood that the user will select a criterion-evoked advertisement, regardless of whether the criterion appears in among content of the webpage, and an expected gain of presenting the criterion-evoked advertisement.

BACKGROUND

One type of advertisement engine selects an advertisement to bepresented in a fillable advertisement space of a given webpage. That is,the given webpage is designed with an empty advertisement space that isdynamically filled when the given webpage is rendered to a recipientdevice (e.g., client computer). Various methodologies might be employedto select an advertisement to be presented in the empty advertisementspace. For example, keywords that are extracted from the given webpagemight be used to evoke advertisements that are related to the keywords,such that a served advertisement might be relevant to content of thegiven webpage. Sometimes, a keyword of the given webpage might evoke anadvertisement that is unlikely to be selected by a recipient-deviceuser. As such, technology that selects advertisements using criteriaother than keywords associated with the given webpage would be useful.

SUMMARY

Embodiments of the invention are defined by the claims below, not thissummary. A high-level overview of various aspects of the invention areprovided here for that reason, to provide an overview of the disclosure,and to introduce a selection of concepts that are further described inthe detailed-description section below. This summary is not intended toidentify key features or essential features of the claimed subjectmatter, nor is it intended to be used as an aid in isolation todetermine the scope of the claimed subject matter.

The present invention is directed to selecting an advertisement to bepresented in an ad space of a webpage. A criterion (e.g., keyword,image, audio element, webpage, search query, ad, etc.) is selected toevoke the advertisement. In an embodiment, the criterion is selectedbased on a relevance of the criterion to a user, and not necessarilybased solely on a relevance to the webpage. For example, a criterionused to evoke the advertisement might include a keyword that is deemedrelevant to a user who will view the webpage. In such an example, thekeyword used to evoke the advertisement might be based on variousfactors, such as the likelihood that the user will select akeyword-evoked advertisement, regardless of whether the keyword appearsin text of the webpage, and an expected gain of presenting thekeyword-evoked advertisement.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrative embodiments of the present invention are described indetail below with reference to the attached drawing figures, wherein:

FIG. 1 is a block diagram depicting an exemplary computing devicesuitable for use in accordance with embodiments of the invention;

FIGS. 2 a-2 d are block diagrams of an exemplary operating environmentin accordance with an embodiment of the present invention; and

FIGS. 3 and 4 are exemplary flow diagrams in accordance with anembodiment of the present invention.

DETAILED DESCRIPTION

The subject matter of embodiments of the present invention is describedwith specificity herein to meet statutory requirements. But thedescription itself is not intended to necessarily limit the scope ofclaims. Rather, the claimed subject matter might be embodied in otherways to include different steps or combinations of steps similar to theones described in this document, in conjunction with other present orfuture technologies. Terms should not be interpreted as implying anyparticular order among or between various steps herein disclosed unlessand except when the order of individual steps is explicitly stated.

Generally, embodiments of the present invention are directed toselecting an advertisement to be displayed on a webpage. For example,often a webpage that is to be served to a recipient device (e.g.,client) includes a blank advertisement space. Prior to rendering thewebpage, an advertisement server selects an advertisement to fill theblank advertisement space.

Referring to FIG. 2 d, information 209 a is communicated from a webpageserver 211 and is depicted in an exploded view to include a webpage 212a. As depicted, webpage 212 a includes a fillable ad space 213 that isidentified as “ad space X9.” Prior to rendering webpage 212 a to arecipient device 214, an ad system 216 selects an advertisement (e.g.,AD2), to be presented in ad space 213. Upon selection of anadvertisement, information 209 b is served to recipient device 214 andincludes webpage 212 b, which includes an advertisement 220 in thepreviously blank fillable ad space. As will be described below in moredetail, in an embodiment of the present invention, a criterion that isused to evoke advertisement 220 is not necessarily included amongcontent 222 a of webpage 212 a.

Having briefly described embodiments of the present invention, we refernow to FIG. 1 in which an exemplary operating environment forimplementing embodiments of the present invention is shown anddesignated generally as computing device 100. Computing device 100 isbut one example of a suitable computing environment and is not intendedto suggest any limitation as to the scope of use or functionality ofinvention embodiments. Neither should the computing environment 100 beinterpreted as having any dependency or requirement relating to any oneor combination of components illustrated.

Embodiments of the invention might be described in the general contextof computer code or machine-useable instructions, includingcomputer-executable instructions such as program modules, being executedby a computer or other machine, such as a personal data assistant orother handheld device. Generally, program modules including routines,programs, objects, components, data structures, etc., refer to code thatperform particular tasks or implement particular abstract data types.Embodiments of the invention might be practiced in a variety of systemconfigurations, including handheld devices, consumer electronics,general-purpose computers, more specialty computing devices, etc.Embodiments of the invention might also be practiced in distributedcomputing environments where tasks are performed by remote-processingdevices that are linked through a communications network.

With reference to FIG. 1, computing device 100 includes a bus 110 thatdirectly or indirectly couples the following devices: memory 112, one ormore processors 114, one or more presentation components 116,input/output ports 118, input/output components 120, and a power supply122. Bus 110 represents what might be one or more busses (such as anaddress bus, data bus, or combination thereof). Although the variousblocks of FIG. 1 are shown with lines for the sake of clarity, inreality, delineating various components is not so clear, andmetaphorically, the lines would more accurately be grey and fuzzy. Forexample, one may consider a presentation component such as a displaydevice to be an I/O component. Also, processors have memory. Werecognize that such is the nature of the art and reiterate that thediagram of FIG. 1 is merely illustrative of an exemplary computingdevice that can be used in connection with one or more embodiments ofthe present invention. Distinction is not made between such categoriesas “workstation,” “server,” “laptop,” “handheld device,” etc., as allare contemplated within the scope of FIG. 1 and reference to “computingdevice.”

Computing device 100 typically includes a variety of computer-readablemedia. By way of example, computer-readable media may comprises RandomAccess Memory (RAM); Read Only Memory (ROM); Electronically ErasableProgrammable Read Only Memory (EEPROM); flash memory or other memorytechnologies; CDROM, digital versatile disks (DVD) or other optical orholographic media; magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, carrier wave or any othermedium that can be used to encode desired information and be accessed bycomputing device 100.

Memory 112 includes computer-storage media in the form of volatileand/or nonvolatile memory. The memory may be removable, nonremovable, ora combination thereof. Exemplary hardware devices include solid-statememory, hard drives, optical-disc drives, etc. Computing device 100includes one or more processors 114 that read data from various entitiessuch as memory 112 or I/O components 120. Presentation component(s) 116present data indications to a user or other device. Exemplarypresentation components include a display device, speaker, printingcomponent, vibrating component, etc.

I/O ports 118 allow computing device 100 to be logically coupled toother devices including I/O components 120, some of which may be builtin. Illustrative components include a microphone, joystick, game pad,satellite dish, scanner, printer, wireless device, etc.

Embodiments of the present invention might be embodied as, among otherthings: a method, system, or set of instructions embodied on one or morecomputer-readable media. Computer-readable media include both volatileand nonvolatile media, removable and nonremovable media, andcontemplates media readable by a database, a switch, and various othernetwork devices. By way of example, computer-readable media comprisemedia implemented in any method or technology for storing information.Examples of stored information include computer-useable instructions,data structures, program modules, and other data representations. Mediaexamples include, but are not limited to information-delivery media,RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM,digital versatile discs (DVD), holographic media or other optical discstorage, magnetic cassettes, magnetic tape, magnetic disk storage, andother magnetic storage devices. These technologies can store datamomentarily, temporarily, or permanently.

Returning to FIG. 2 d, a computing environment that includes networkedcomponents is depicted and is identified generally by reference numeral210. Computing environment 210 includes webpage server 211, ad system216, and recipient device 214. Components of computing environment 210communicate to execute various functions, such as when recipient device214 requests a webpage, which is served by webpage server 211, enhancedby ad system 216, and ultimately rendered to recipient device 214. In anembodiment of the present invention, network 224 facilitatescommunication with other webpage-rendering components (not shown) thatperform other functions required to provide a webpage from a webpageserver to recipient device 214. FIG. 2 d depicts a computing environmentin which various types of evoking criteria might be used to evoke anadvertisement. Exemplary evoking criteria might include a keyword, animage, an audio element, and an advertisement. Other exemplary evokingcriteria (not shown) might include a video, a webpage, and a searchquery.

Ad system 216 includes various components that communicate by way ofnetwork 224. For example, ad system 216 includes an ad index 226, whichstores information 227 including advertisements to be presented inwebpages rendered to recipient device 214. In one embodiment, adselector 264 functions to select an advertisement for presentation in afillable ad space. For example, upon receipt of webpage 246 a havingfillable ad space X5 244, ad selector 264 identifies a criterion (e.g.,keyword, audio, image, etc.), which is usable to evoke an advertisement.As described in more detail below, criteria might be identified usingvarious methodologies. For example, ad selector 264 might extract akeyword or an image from content 247 of webpage 246 a. In such anexample, when an ad to be displayed on a given webpage is evoked by acriterion that is extracted from the given webpage, the ad might becategorized as a contextual advertisement. In another example, adselector 264 might reference criteria evaluator 284 d (described in moredetail below) in order to identify an evoking criterion. Once acriterion is identified, ad selector 264 references ad index 226 usingthe identified criterion. An advertisement that is relevant to theidentified criterion is retrieved, such that the identified criterion“evokes” the advertisement. In a further embodiment, ad selector 264provides information to statistic tracker 240 describing theadvertisement selection.

In embodiments of the present invention, network (e.g., Internet)activities, such as browsing or search activities of a user of recipientdevice 214, are used to identify criteria that are usable at a futureinstant in time to evoke an advertisement of a webpage. User networkactivities (e.g., browsing and searching) might be tracked using variousidentifiers such as a machine id included in a browser cookie or a loginid, which allows tracking of a user regardless of what recipient devicethe user is logged into. Network activities might be tracked andanalyzed in a variety of ways to identify criteria that are associatedwith a user of recipient device 214. In one embodiment, criteria areidentified when a webpage or search-results page (also referred to as“SRP”) having a criteria-evoked advertisement is rendered to recipientdevice 214. For example, criteria that are identified might include anycriterion that evokes an advertisement; any criterion that was a sourceof a potential advertisement, regardless of whether the potentialadvertisement was ultimately evoked; and any criterion that is includedin a webpage, but that was not evaluated to potentially evoke anadvertisement. In this respect, embodiments of the present inventionrecognize that while a criterion might not be used to evoke anadvertisement, which is presented to a user, the criterion might stillbe relevant to the user when future advertisement opportunities arise.

In another embodiment, criteria are identified throughout a definedperiod of time. For example, criteria might be identified based on allbrowsing or search activities of recipient device 214 taking place inthe course of one day, one week, or any other desired period of time.Alternatively, criteria might be identified until a defined number ofcriteria is identified. For example, criteria might be identified fromnetwork activities until one hundred criteria have been identified. Inanother embodiment, a number of criteria to be identified is based on acombination of a defined number and a defined time duration. Forexample, criteria might be identified until the earlier of one-hundredcriteria are identified or network activities have been tracked for oneweek. As such, in various embodiments of the present invention, becausemultiple criteria are identified, the criteria are evaluated andcompared to one another to identify a criterion that is deemed mostdesirable. A criterion might be deemed most desirable if the criterionevokes valuable advertisements (e.g., advertisements that are likely tobe selected by a recipient device user).

In a further embodiment of the present invention, criteria that havebeen identified from network activities of recipient device are scored,thereby enabling criteria ranking and identification of most favorablecriteria. For example, as described in more detail below, a criteriascore might be determined using statistics maintained in statistictracker 240. Moreover, a criteria score might depend on other factors,such as whether a criterion was a source of a potential advertisement,whether a criterion was used to evoke an advertisement, and, if thecriterion was used to evoke an advertisement, whether the advertisementwas selected.

Accordingly, an embodiment of the present invention includes statistictracker 240, which tracks statistics 242 related to a criterion and afillable advertisement space (e.g. ad space X5 244). As will bedescribed in more detail below, statistics 242 are usable bycriteria-stat generator 270 d to calculate values associated with agiven criterion. For example, using values collected by statistictracker 240, criteria-stat generator 270 d quantifies a relevance of agiven criteria to a user. In embodiments of the present invention, arelevance of a criterion to a user indicates an association strength ofthe criterion to the user, the association strength sometimesinfluencing the likelihood that the user will select an advertisementevoked by the criterion. In this respect, a higher relevance of acriterion to a user suggests a higher likelihood that the user willselect an ad evoked by the criterion, as compared to a differentcriterion with a lower relevance to the user. Embodiments of the presentinvention utilize different measures of relevance. For example, acontextual relevance suggests an association strength between a user anda criterion that is determined in a context of when the criterion isserved to the user, such as when the criterion is served among contentof a webpage. Another type of relevance includes learned relevance,which suggests an association strength between a user and a criterionthat is recognized (e.g., by using a machine learning algorithm) basedon an aggregation of contextual-relevance values.

In embodiments of the invention, values calculated by criteria-statgenerator 270 d are stored in user-criteria database 266 d and areusable by criteria evaluator 284 d to determine whether a givencriterion should be used to evoke an advertisement. For example,criteria evaluator 284 d might facilitate an auction between variouscriteria using values calculated by criteria-stat generator 270 d.

Referring now to FIG. 2 a, an embodiment of the present invention isdepicted in which a keyword is used as a criterion to evoke anadvertisement. FIG. 2 a depicts a version of the environment depicted inFIG. 2 d in which some elements are more specifically depicted toevaluate a keyword as a type of criterion. For example, user-keyworddatabase 266 a of FIG. 2 a is a specific version or type of auser-criteria database 266 d of FIG. 2 d because a keyword is one typeof criterion. Accordingly, user-keyword database 266 a might be one ofmany databases within user-criteria database 266 d Likewise,keyword-stat generator 270 a and keyword evaluator 284 a are specifictypes of (and might be sub-components of) criteria-stat generators andcriteria evaluators, respectively.

In one embodiment, an exemplary statistical category includes a numberof times an advertisement evoked by a particular keyword is presented toany user of any recipient device in a particular fillable advertisementspace (e.g., ad space 244 of webpage 246 a identified as “ad space X5”).That is, in the course of a period of time (e.g., 1 day) a particularwebpage (e.g., webpage 246 a) having a fillable advertisement space(e.g., ad space X5 244) might be rendered 1000 times total to 750different recipient devices. Of those 1000 renderings, an advertisementevoked by a particular keyword (e.g., AD2 248 evoked by KW2) might bepresented in the fillable advertisement space a total of 100 times. Inthis example, during those 900 other renderings, one or more differentadvertisements (e.g., AD1 232 and AD3 241) might have been presented inthe fillable advertisement space. In FIG. 2 a, column 234 is identifiedas “Evoked Ad Served” and records a number of times a keyword-evokedadvertisement (e.g., AD2 248) is presented in ad space X5 244. Asindicated above, upon selection of an advertisement to be presented in afillable ad space, ad selector 264 notifies statistic tracker of theselection, thereby allowing statistic tracker 240 to update informationunder column 234.

Another exemplary statistical category (depicted under column 236 titled“Evoked Ad Clicked”) includes a number of times an advertisement (e.g.,AD2 248), which is evoked by a particular keyword, is selected by anyrecipient-device user when the advertisement is presented in aparticular advertisement space (e.g., ad space X5 244). In embodimentsof the present invention a recipient-device user might “select” anadvertisement in various ways, such as by clicking the advertisementwith an input device (e.g., mouse, touch surface, etc.). In anembodiment of the present invention, feedback 250 is provided, eitherexpressly or inherently, from recipient device 214 to ad system 216. Forexample, feedback 250 might be triggered by a selection of anadvertisement (e.g., AD2 248) by a recipient-device user. Alternatively,feedback 250 might be inherently provided when an advertisement (e.g.,AD2 248) is not selected on a webpage (e.g., webpage 246 b), such aswhen a recipient-device user navigates away from the webpage (e.g.,webpage 246 b) without selecting the advertisement (e.g., AD2 248). Inan exemplary embodiment, if webpage 246 b is presented with AD2 248(evoked by KW2) one-hundred times total to various recipient devices,AD2 248 might be selected five times, as reflected by information 252.Of those 100 impressions, some might be presented to the same recipientdevice more than once. Alternatively, each of the 100 impressions mightbe unique (i.e., presented to 100 different recipient devices).Moreover, each of the five selections might have been executed by fivedifferent recipient-device users, or alternatively, a recipient-deviceuser might have executed multiple of the five selections.

Another exemplary statistical category (depicted under column 254 titled“Evoked Ad Served to Clickers”) includes a number of times anadvertisement, which is evoked by a particular keyword, is served in aparticular fillable advertisement space to any user that selected (e.g.,clicked) the advertisement. For example, an advertisement evoked by KW2(e.g., AD2 248) might have been selected five times total by threedifferent users when served with webpage 246 b in ad space X5 244.However, AD2 248 might have actually been served in ad space X5 244 tentimes total to those three different users. In this case, as reflectedby information 255, ten is the number of times AD2 248 is served in adspace X5 244 to any user that selected AD2 248.

Another exemplary statistic (depicted under column 258 titled“Source—not used”) includes a number of times a keyword was a source ofa potential keyword-evoked advertisement, which was not selected to bepresented at a particular ad space (e.g., ad space X5 244). For example,KW1 is included among text 247 of webpage 246 a, such that KW1 mighthave been source to evoke AD1 232. However, as depicted by webpage 246b, AD1 232 was not selected to be presented at ad space X5 244. In oneembodiment, a keyword is “available to evoke” an advertisement to bepresented with a webpage when the keyword is included among text of thewebpage. A keyword that is available to evoke an advertisement might notbe used to evoke the advertisement at the specified ad space for avariety of reasons. For example, an advertisement might not be locatedor the keyword might not be deemed as favorable as a different keyword.Alternatively, the keyword might be used to evoke an ad that is renderedin a different ad space. That is, a keyword is a “source” of anadvertisement when the keyword is evaluated (e.g., by ad selector 264 orkeyword evaluator 290) to potentially evoke an advertisement, regardlessof whether or not the keyword is ultimately used to evoke anadvertisement. On the other hand, a keyword is not deemed a source wherethe keyword is available (e.g., in the webpage text) but is notevaluated to potentially evoke an advertisement.

In embodiments of the present invention, network (e.g., Internet)activities, such as browsing or search activities of a user of recipientdevice 214, are used to identify a user keyword that is relevant to auser and that usable at a future instant in time to evoke anadvertisement. For example, KW2 268, which is associated with a user inuser-keyword database 266 a and has been deemed relevant to the user,might be used to evoke AD2 220 in webpage 212 b, even though KW2 268 isnot included within text 222 a. User network activities (e.g., browsingand searching) might be tracked using various identifiers such as amachine I.D. included in a browser cookie or a login I.D., which allowstracking of a user regardless of what recipient device the user islogged into.

Network activities might be tracked and analyzed in a variety of ways toidentify user keywords (e.g., KW1 269) that are associated with a userof recipient device 214. In one embodiment, a user keyword is identifiedwhen a webpage or search-results page (also referred to as “SRP”) havinga keyword-evoked advertisement is rendered to recipient device 214. Forexample, webpage 246 b that is rendered to recipient device 214 includesAD2 248 evoked by KW2. As such, various user keywords might beidentified from webpage 246 b, including any keyword that was used toevoke an advertisement of webpage 246 b (there might be otherkeyword-evoked advertisements in addition to AD2 248); any keyword thatwas a source of a potential advertisement, regardless of whether thepotential advertisement was ultimately evoked; and any keyword that isincluded in webpage 246 b, but that was not evaluated to potentiallyevoke an advertisement. Referring to webpage 246 b, KW2 is a userkeyword as KW2 evoked AD2 248. In addition, KW1, KW3, and KW4 are alsouser keywords. In this respect, embodiments of the present inventionrecognize that while a keyword might not be used to evoke anadvertisement, which is presented to a user, the keyword might still berelevant to the user when future advertisement opportunities arise.

In another embodiment, user keywords are identified throughout a definedperiod of time. For example, user keywords might be identified based onall browsing or search activities of recipient device 214 taking placein the course of one day, one week, or any other desired period of time.Alternatively, user keywords might be identified until a defined numberof user keywords are identified. For example, user keywords might beidentified from network activities until one hundred user keywords havebeen identified. In another embodiment, a number of user keywords to beidentified is based on a combination of a defined number and a definedtime duration. For example, user keywords might be identified until theearlier of one-hundred user keywords are identified or networkactivities have been tracked for one week. As such, in variousembodiments of the present invention, because multiple user keywords areidentified, the user keywords are evaluated to identify a user keywordthat is deemed most desirable. A user keyword might be deemed mostdesirable if the user keyword evokes valuable advertisements (e.g.,advertisements that are likely to be selected by a recipient deviceuser).

In a further embodiment of the present invention, user keywords thathave been identified from network activities of recipient device arescored, thereby enabling user-keyword ranking and identification of mostfavorable user keywords. For example, as described in more detail below,a user-keyword score (e.g., stored under column 275) might be determinedusing statistics maintained in statistic tracker 240. Moreover, auser-keyword score might depend on other factors, such as whether akeyword was a source of a potential advertisement, whether a keyword wasused to evoke an advertisement, and, if the keyword was used to evoke anadvertisement, whether the advertisement was selected.

In an additional embodiment of the present invention, a user-keywordscore is based, at least in part, on a measured click-through-rate(mCTR). An mCTR is a value that quantifies a relevance (e.g., contextualrelevance) of the user keyword as the user keyword relates to arecipient-device user in a context of when a webpage including akeyword-evoked ad is served to the recipient device, the keywordtypically extracted from the webpage content. For example, when webpage246 b is served with AD2 248 to recipient device 214, an mCTR of KW2 249quantifies a relevance of KW2 249 to a recipient-device user in thecontext of when webpage 246 b is served with AD2 248. Likewise, whenwebpage 246 b is served with AD2 248 to recipient device 214, adifferent mCTR of KW1 251 quantifies a relevance of KW1 251 to arecipient-device user in the context of when webpage 246 b is servedwith AD2 248. In an embodiment of the present invention, an mCTRquantifies a contextual relevance of a criterion to a user as the mCTRsuggests an association strength between a user and a criterion that isdetermined in a context of when the criterion is served to the user,such as when the criterion is served among content of a webpage. In afurther embodiment of the present invention, a keyword-stat generator270 a functions to calculate an mCTR of a given user keyword. Anexemplary keyword-stat generator 270 a is depicted in more detail inFIG. 2 b and includes an mCTR calculator 280. In an embodiment of thepresent invention, calculation of an mCTR of a user keyword depends onwhether the user keyword was a source of a potential advertisement;whether a keyword was used to evoke an advertisement; and, if thekeyword was used to evoke an advertisement, whether the advertisementwas selected.

In FIG. 2 b, column 271 under mCTR calculator 280 depicts variousformulas that might be used to calculate an mCTR of a user-keywordpairing, depending on how the keyword relates to an advertisement thatwas rendered to recipient device. That is, the various formulas might beused to calculate an mCTR of a given user keyword as the given userkeyword relates to a recipient-device user when the particularrecipient-device user engages in network activity that exposes the userto the user keyword. Exemplary pairings are depicted under column 277that were generated based on rendering webpage 246 b (FIG. 2 a), whichincluded KW1, KW2, and KW3, to recipient device 214. Recipient device214 is identified by “55.11.” Pairs listed under column 277 include(i.e., are specific to) a user and a keyword (e.g., 55.11 and KW2)because the mCTR quantifies a relevance of the keyword to the user.Under column 277, pair 55.11 and KW2 are listed twice because the mCTRvalue of KW2 as it relates to 55.11 depends on whether an advertisementevoked by KW2 was selected by 55.11.

As depicted in field 272 under mCTR calculator 280, when anadvertisement that is evoked by a particular keyword and that ispresented in a particular fillable ad space (e.g., in FIG. 2 a AD2 248of webpage 246 b presented in ad space X5 244) is not selected by arecipient-device user, the mCTR of the user-keyword pairing (e.g., user55.11 and KW2) is represented by a ratio: (SEL/IMP). In an embodiment ofthe invention “SEL” is a number of times the keyword-evokedadvertisement (e.g., AD2 248) is selected by any user of any recipientdevice when the keyword-evoked advertisement (e.g., AD2 248) is servedin the particular ad space (e.g., ad space X5 244). In a furtherembodiment, IMP is a number of times the keyword-evoked advertisement(e.g., AD2 248) is served, regardless of whether it is selected, to anyrecipient device in the particular fillable ad space (e.g., ad space X5244). According to an example provided by FIG. 2 b, SEL of KW2 at adspace X5 is five, as depicted in field 252, i.e., an ad evoked by KW2was selected a total of five times by any user of any recipient devicewhen the ad evoked by KW2 was served in ad space X5 244. Moreover, IMPof KW2 at ad space X5 is 100, as depicted in field 256, i.e., an adevoked by KW2 was served in ad space X5 to any recipient device a totalof 100 times. As such, in the example provided by FIG. 2, when AD2 248(FIG. 2 a) is not selected, an mCTR (55.11, KW2) is equal to 0.05.

Field 273 under mCTR calculator 280 depicts when an advertisement thatis evoked by a keyword and that is presented in a particular fillable adspace (e.g., AD2 248 of webpage 246 b presented in ad space X5 244) isselected by a recipient-device user, the mCTR of the user-keywordpairing is represented by a ratio: (SEL/CLI). As previously described,in an embodiment of the invention “SEL” is a number of times thekeyword-evoked advertisement (e.g., AD2 248) is selected (e.g., clicked)by any user of any recipient device when the keyword-evokedadvertisement (e.g., AD2 248) is served in the particular ad space(e.g., ad space X5 244). In a further embodiment, CLI is a number oftimes the keyword-evoked advertisement (e.g., AD2 248) is served at thead space to all users that selected the keyword-evoked advertisement(e.g., AD2 248). According to an example provided by FIG. 2 b, SEL ofKW2 at ad space X5 is five (as depicted in field 252), i.e., an adevoked by KW2 was selected a total of five times by any user of anyrecipient device when the ad evoked by KW2 was served in ad space X5244. Moreover, CLI of KW2 at ad space X5 is ten, as depicted in field255, i.e., an ad evoked by KW2 was served to all recipient devices thatselected the ad evoked by KW2 a total of 10 times.

Field 274 of mCTR calculator 280 depicts that when a keyword-evokedadvertisement presented in a particular fillable ad space (e.g., AD2 248of webpage 246 b presented in ad space X5 244) is not evoked by a userkeyword (e.g., KW1), but the user keyword (e.g., KW1) was a source tothe ad selector, which is able to evoke an advertisement (perhapsevoking an alternative advertisement, such as AD1), the mCTR of theuser-keyword pairing (e.g., 55.11 and KW1) is calculated using a formularepresented by: mCTR=(SEL/IMP)*(IMP/SOU)^(α). In an embodiment,(SEL/IMP) is as described herein above; and “SOU” is equal to the numberof times the user keyword (e.g., KW1) was a source to evoke thealternative advertisement (e.g., AD1), regardless of whether thealternative advertisement (e.g., AD1) was served. Moreover, “α” is aparameter that is learned by the system. In one embodiment, α includes adefault value. In one embodiment, the default value is 0.5. In anexample provided in FIG. 2 b, SEL/IMP of KW1 is 0.1 (i.e., 10/100) andIMP of KW1 is 100 (as depicted in field 257), Moreover, SOU of KW1 is200 (as depicted by combination of fields 257 and 259), i.e., KW1 was asource to evoke an alternative advertisement 200 times, 100 of which thealternative advertisement was evoked.

Field 276 of mCTR calculator 280 depicts that when a keyword-evokedadvertisement presented in a particular fillable ad space (e.g., AD2 248of webpage 246 b presented in ad space X5 244) is not evoked by a userkeyword (e.g., KW3) and the user keyword was not a source to evoke analternative advertisement (e.g., AD3), the mCTR is calculated using aformula represented by: mCTR=((SEL/IMP)*(IMP/SOU)^(α))* (SOU/TOT)^(β).As described above, a keyword is not a source to evoke an advertisementwhen the keyword is not evaluated (e.g., entered into an auction) to beselected to evoke an advertisement. In an embodiment of the presentinvention, ((SEL/IMP)* (IMP/SOU)^(α)) and SOU are as described abovewith respect to field 274. In a further embodiment, TOT is equal to anumber of times the fillable advertisement space was served to any userof any recipient device and β is a parameter that is learned. In oneembodiment, β includes a default value. In one embodiment the defaultvalue is 0.5. For example, TOT might be determined for a given timeperiod (e.g., one week or whatever duration is required to identify adefined number of user keywords) during which browsing activity is beingmonitored. In the example provided in FIG. 2 b, ad space X5 was served1000 times total to any user of any recipient device, such that the mCTRof the pair (55.11, KW3) is equal to((15/100)*(100/150)^(α))*(150/1000)^(β).

In an embodiment of the present invention, formulas (such as thosedepicted in fields 272, 273, 274, and 276) that are used to determine anmCTR value either discount or enhance a base mCTR value. For example, abase mCTR might be established in situations in which a user is exposedto a keyword-evoked advertisement but does not select the keyword evokedadvertisement. An assumption might be made that users that are exposedto a particular keyword-evoked ad at a particular advertisement spaceshare a similar predisposition to that particular keyword. In anembodiment of the present invention, the ratio (SEL/IMP) establishes abase mCTR value. The base mCTR might be enhanced to describe users thatselected the advertisement. That is, by enhancing the base mCTR value astronger relevance might be predicted between a user and a keyword thatevoked the selected advertisement. In an embodiment of the presentinvention, a formula that enhances the mCTR value includes (SEL/CLI).Moreover, the base mCTR might be discounted in situations where a useris not exposed to a keyword-evoked ad, but the keyword was a source toevoke an advertisement. In an embodiment, a formula that discounts themCTR value includes: (SEL/IMP)*(IMP/SOU)^(α). Furthermore, the base mCTRmight be further manipulated to account for situations in which akeyword is not even a source of a potential advertisement, such that aformula that further manipulates the mCTR includes((SEL/IMP)*(IMP/SOU)^(α))*(SOU/TOT)^(β).

In a further embodiment of the present invention, other factors might betaken into consideration when calculating an mCTR of a givenuser-keyword pairing. For example, if an advertisement evoked by aparticular keyword was presented in a fillable ad space that is lessprominently positioned (e.g., lower on a webpage), the mCTR of thatuser-keyword pairing might be enhanced (as the position already figuredin a discount). In this manner, the mCTR formula takes into accountinferences that might be drawn regarding relevance of a user keyword,i.e., a user keyword might be given a higher mCTR if it was used toevoke an advertisement at a less desirable fillable ad space.

In further embodiments, a user might navigate to a webpage more thanonce, or might navigate to multiple webpages that include a samekeyword, such that multiple mCTRs of a given user-keyword pair aregenerated. For example, if recipient device 214 navigates to webpage 212b on multiple occasions during a time period when navigation is beingtracked, content including KW5 will have been rendered to recipientdevice 214 more than once, such that multiple mCTRs related to the pair(55.11, KW5) might be calculated. In one embodiment, the highest mCTR ofa given user-keyword pair is selected as a final mCTR of the givenuser-keyword pair. Alternatively, an average mCTR of all mCTR values isutilized as a final mCTR of the given user-keyword pair.

In a further embodiment, the mCTR value of a user-keyword pair is usedto predict whether an advertisement served with a webpage will beselected by a recipient-device user when the advertisement is evoked bythe user keyword. For example, in one embodiment, an mCTR is used tocalculate a user-behavior text-independent click-through-rate(hereinafter “uCTR”). In an embodiment, a uCTR quantifies a learnedrelevance, which suggests an association strength between a user and acriterion that is recognized (e.g., by using a machine learningalgorithm) based on one or more measured or observed statistics. Anexample of measured statistics includes an aggregation ofcontextual-relevance values. In a further embodiment, a uCTR of a givenuser-keyword pairing might be determined by applying a link function toone or more mCTR values. In one embodiment, uCTR is calculated by usinga Mobius transformation, such that the formula (az+b)/(cz+d) is appliedto one or more mCTR values, wherein a, b, c, and d are learnedparameters and z is the mCTR of the given user-keyword pairing. Forillustrative purposes, FIG. 2 b includes a uCTR calculator 281, whichdetermines a uCTR of a pairing. In a further embodiment, inferences aredrawn from a uCTR of a given pairing as to whether an advertisementserved with a webpage will be selected by a recipient-device user whenthe advertisement is evoked by the user keyword, which is not includedamong text of the webpage. Once a uCTR has been determined, the uCTR isassociated with the user-keyword pairing, such as in user-keyworddatabase 266 a under column 293. For example, line 285 illustrates thatinformation generated by uCTR calculator 281 is communicated touser-keyword database 266 a.

Moreover, the uCTR is utilized in other respects to evaluate a givenuser-keyword pairing. For example, as described above, user keywords arescored to enable user-keyword ranking and identification of mostfavorable user keywords. In one embodiment, keyword-stat generator 270 aincludes a user-keyword scorer 282, which further processes a uCTR todetermine a keyword score and to assess a value of serving a given useran advertisement evoked by a particular keyword. In one embodiment, todetermine a keyword score, a uCTR is multiplied by a cost-per-clickvalue (also referred to as “CPC”) (i.e., an expected cost-per-click of akeyword-evoked advertisement), the product of which is reduced by anexpected opportunity cost (also referred to as “EOC”) of not serving anadvertisement evoked by a webpage keyword, which is included among textof the webpage. In a further embodiment, the product might be multipliedby 1000 to translate the product to a cost-per-mille value. Bymultiplying a uCTR by CPC, and reducing the product by an EOC, anexpected net gain (also referred to as “ENG”) value is inferred, i.e.,an expected net gain of serving to a particular user a webpage with anadvertisement evoked by a given keyword, which is not included amongtext of the webpage. In one embodiment, the ENG of a user-keywordpairing is utilized as a keyword score to compare the user-keywordpairing to other user-keyword pairings. Such a comparison might be mostappropriate where keywords are equally likely to evoke an advertisement.In such an embodiment, the invention essentially compares the ENG of onepairing against the ENG of an alternative pairing to determine whichpairing is more favorable. In a further embodiment, where user keywordsare not equi-likely to evoke an advertisement, the expected-net-gainvalue is multiplied by an expected number of impressions, which might beuser dependent. Once a score has been determined, the score isassociated with the user-keyword pairing, such as in user-keyworddatabase 266 a. For example, line 295 illustrates that informationgenerated by user-keyword scorer 282 is communicated to user-keyworddatabase 266 a.

Referring to FIG. 2 a, KW2, KW1, and KW3, which are stored inuser-keyword database 266 a, have been scored and ranked from a mostfavorable value to a least favorable value. KW2, KW1, and KW3 have beenassociated with a user (i.e., 55.11), and KW2 has been identified as auser keyword that has a favorable expected value (e.g., ENG reflected byfavorable score) and that might be selected by a recipient-device user(e.g., as suggested by uCTR). In one embodiment, the aggregation andscoring of user keywords is performed offline, thereby creating a listof user keywords that might be loaded as an active file at runtime. Forexample, upon receiving webpage 212 a, which is to be rendered torecipient device 214, a determination is made that ad space X9 213should be filled. As previously described, when selecting anadvertisement to be presented in ad space X9 213, keywords areidentified that might be used to evoke the advertisement. In oneembodiment, to identify keywords the list of user keywords in the activefile is referenced, thereby retrieving keywords that might not beincluded in among text 222 a of webpage 212 a.

In a further embodiment, upon identification of keywords that are usableto evoke an advertisement (e.g., AD2 220) to be presented in ad space X9213, an auction is held to determine which of the keywords should beused to evoke the advertisement. Referring to FIGS. 2 a and 2 c, akeyword evaluator 284 a is depicted in more detail and depicts how anauction might be performed to select an advertisement to be presented ina target webpage. In one embodiment, keyword evaluator 284 a comparesone or more keywords (e.g., KW2 286) that have been previouslyassociated with a user and one or more keywords (e.g., KW5 288) or othercriterion that are included among the text, such that a keyword that isultimately selected to evoke an advertisement is not necessarilyincluded among the text. That is, the one or more keywords that havebeen previously associated with a user are not required to be includedamong the text, although they might be included among the text. In afurther embodiment a respective auction rank (e.g., ranks 287 and 289)is calculated for each of the keywords.

For example, an auction rank of the keyword (e.g., KW5) included in thetext (e.g., text 222 a) might be determined based, at least in part, ona predicted click-through-rate (pCTR) (e.g., 290) and a keyword-to-pagerelevance score (e.g., 292). A pCTR is a value that suggests a generalrelationship between a keyword and a particular ad, e.g., pCTR valuesuggests average rate at which advertisements evoked by the keyword areclicked. A pCTR value does not take into consideration a relevance of akeyword to a particular user and does not take into account a relevanceof a keyword to a webpage. On the other hand, a keyword-to-pagerelevance score (also referred to as “PgREL”) is a factor that takesinto account a relevance of a keyword to a webpage, such that keywordsmore germane to a main subject of a webpage have a more favorablekeyword-to-page relevance score. As such, in an embodiment of thepresent invention, an auction rank of a keyword that is included amongtext of a webpage is determined by applying a formula represented by:auction rank(contextual keyword)=bid*pCTR* PgREL. Such an embodiment isdepicted in field 294 of keyword evaluator 284 a.

In a further embodiment of the present invention, the value uCTR/pCTR isassociated with the user-keyword pair to fill in for the page-keywordrelevance (PgREL), so that an auction rank of a keyword that has beenpreviously associated with a user and that is not necessarily includedamong text of a webpage is determined by applying a formula representedby: auction rank(user-associated keyword)=bid*pCTR* (uCTR/pCTR). In suchan auction-ranking formula, the pCTR is canceled and the auction rank isequal to the product of a bid and a uCTR value. Such an embodiment isdepicted in field 291 of keyword evaluator 284 a. Line 297 depicts theuCTR value being used in an auction-ranking formula.

In an alternative embodiment, a keyword or other evoking criterion mighthave been previously associated with a user and might also be includedamong text of a webpage, such that an alternative auction-rankingformula is applied in which the uCTR, the pCTR, and the PgREL are allconsidered when determining whether to use the keyword to evoke anadvertisement. For example, KW3 207 is associated with user 55.11 inuser-keyword database 266 a and KW3 is also included among text 222 a ofwebpage 212 a, such that both the relevance of KW3 to user 55.11 and therelevance of KW3 to webpage 212 a might be taken into consideration whendetermining whether KW3 should be used to evoke an advertisement.

In an embodiment of the present invention, a keyword that enters anauction and is determined to have the most favorable auction rank isselected as a keyword to evoke an advertisement. For example, if KW2enters an auction and is determined to have a most favorable auctionrank, KW2 is used to evoke an advertisement. Such an exemplary scenariois depicted by webpage 212 b, which includes AD2 220 evoked by KW2.

Referring to FIG. 3, an embodiment of the present invention is directedto one or more computer-readable media having computer-executableinstructions embodied thereon that, when executed, cause a computingdevice to perform a method (identified generally by reference numeral310) of selecting an advertisement to be displayed on a webpage. Indescribing method 310, reference is made to FIGS. 2 a-2 d for exemplarypurposes. Method 310 includes receiving 312 the webpage (e.g., webpage212 a of FIG. 2 d) that is to be served to a recipient device and thatincludes a fillable advertisement space (e.g., ad space X9 213), whereinthe webpage includes a current-webpage criterion among content (e.g.,text 222 a) of the webpage. A current-webpage criterion might includevarious elements that are included among content of the webpage and thatare usable to evoke an advertisement. Exemplary current-webpage criteriainclude a keyword, an image, an audio element, a video, anadvertisement, and a search query.

At step 314, a user-behavior click-through-rate (uCTR) of auser-associated criterion (e.g., keyword, image, video, audio, ad,search query, etc.) is retrieved, the user-associated criterion beingpreviously available to evoke a prior advertisement that was previouslyserved to a user of the recipient device, wherein the uCTR quantifies arelevance of the user-associated criterion to the user. A uCTR might beretrieved from a user-criteria database. Moreover, a uCTR might beretrieved from an active file that includes a set of uCTRs, which areranked to identify one or more user-associated criteria that aredesirable to evoke an advertisement.

Step 316 includes, based at least in part on the uCTR, evoking with theuser-associated criterion, instead of the current-webpage criterion, theadvertisement to be served in the fillable advertisement space.

Referring to FIG. 4, another embodiment is directed to a method(identified generally by reference numeral 410), which is facilitated bya processor and computer-readable media, of selecting an advertisementto be displayed on a webpage. The method 410 includes at 412, serving toa recipient device an initial webpage (e.g., webpage 246 b of FIG. 2 a)having an initial advertisement (e.g., AD2 248) and a webpage keyword(e.g., KW2), which is included among text (e.g., text 247) of theinitial webpage, wherein the initial advertisement is served in aninitial fillable advertisement space. Step 414 includes calculating ameasured click-through-rate (mCTR) that quantifies a relevance of thewebpage keyword (e.g., KW2) to a recipient-device user in a context ofwhen the initial webpage (e.g., webpage 246 b) is served. For example,KW2 249 might be identified among text of webpage 246 b, such thatkeyword-stat generator 270 a calculates an mCTR of KW2 249 using anappropriate formula from the exemplary formulas depicted in fields 272,273, 274, and 276 of FIG. 2 b.

Step 416 includes using the mCTR to calculate a user-behaviorclick-through-rate (uCTR), which suggests whether a subsequentadvertisement (e.g., 220) served with a subsequent webpage (e.g.,webpage 212 b) will be selected by the recipient-device user when thesubsequent advertisement is evoked by the webpage keyword (e.g., KW2).For example, the mCTR that was calculated for KW2 might be used by uCTRcalculator 281 to calculate a uCTR.

At step 418, an auction is conducted between the webpage keyword (e.g.,KW2) and a current-webpage keyword (e.g., KW5), which is included amongthe text (e.g., 222 a) of the subsequent webpage (e.g., webpage 212).For example, keyword evaluator 284 a might compare KW2 and KW5 byapplying one or more appropriate auction-ranking formulas as depicted infields 294 and 291. Pursuant to method 410, a result of the auction isat least in part determined using the uCTR of the webpage keyword, andbased on the result, the webpage keyword is used, instead of thecurrent-webpage keyword, to evoke the subsequent advertisement, which isserved to the recipient device.

Many different arrangements of the various components depicted, as wellas components not shown, are possible without departing from the scopeof the claims below. Embodiments of our technology have been describedwith the intent to be illustrative rather than restrictive. Alternativeembodiments will become apparent to readers of this disclosure after andbecause of reading it. Alternative means of implementing theaforementioned can be completed without departing from the scope of theclaims below. Certain features and subcombinations are of utility andmay be employed without reference to other features and subcombinationsand are contemplated within the scope of the claims.

1. One or more computer-readable media having computer-executableinstructions embodied thereon that, when executed, cause a computingdevice to perform a method of selecting an advertisement to be displayedon a webpage, the method comprising: receiving the webpage that is to beserved to a recipient device and that includes a fillable advertisementspace, wherein the webpage includes a current-webpage criterion amongcontent of the webpage; retrieving a user-behavior click-through-rate(uCTR) of a user-associated criterion, which was available to evoke aprior advertisement that was previously served to a user of therecipient device, wherein the uCTR quantifies a relevance of theuser-associated criterion to the user; and based at least in part on theuCTR, evoking with the user-associated criterion, instead of thecurrent-webpage criterion, the advertisement to be served in thefillable advertisement space.
 2. The one or more computer-readable mediaof claim 1, wherein the uCTR suggests whether the advertisement servedwith the webpage will be selected by the user when the advertisement isevoked by the user-associated criterion.
 3. The one or morecomputer-readable media of claim 1, wherein the prior advertisement wasserved in a prior advertisement space of a prior webpage; wherein theuCTR is calculated by applying a link function to a measuredclick-through-rate (mCTR), such that the uCTR quantifies a learnedrelevance of the user-associated criterion to the user, and wherein themCTR quantifies a contextual relevance of the user-associated criterionto the user in a context of when the prior webpage was served to theuser.
 4. The one or more computer-readable media of claim 3, wherein theuCTR is determined using a formula represented by:uCTR=(az+b)/(cz+d); wherein z represents the mCTR of a pairing of theprior advertisement space and the user-associated criterion; and whereina, b, c, and d represent learned coefficients.
 5. The one or morecomputer-readable media of claim 1, wherein the user-associatedcriterion is available to evoke the prior advertisement when theuser-associated criterion is included among content of a prior webpagethat was served to the user together with the prior advertisement. 6.The one or more computer-readable media of claim 1 further comprising,conducting an auction between the user-associated criterion and thecurrent-webpage criterion, wherein a first auction rank of theuser-associated criterion is equal to a product of a first bid and theuCTR, and wherein the first rank is more favorable than a second rank ofthe current-webpage criterion, such that, based at least in part on theuCTR, the user-associated criterion is used to evoke the advertisement.7. The one or more computer-readable media of claim 6, wherein theuser-associated criterion is not included among content of the webpage.8. A method, which is facilitated by a processor and computer-readablemedia, of selecting an advertisement to be displayed on a webpage, themethod comprising: serving to a recipient device an initial webpagehaving an initial advertisement and a webpage keyword, which is includedamong text of the initial webpage, wherein the initial advertisement isserved in an initial fillable advertisement space; calculating ameasured click-through-rate (mCTR) that quantifies a relevance of thewebpage keyword to a recipient-device user in a context of when theinitial webpage is served; using the mCTR to calculate a user-behaviorclick-through-rate (uCTR), which suggests whether a subsequentadvertisement served with a subsequent webpage will be selected by therecipient-device user when the subsequent advertisement is evoked by thewebpage keyword; and conducting an auction between the webpage keywordand a current-webpage keyword, which is included among the text of thesubsequent webpage, wherein a result of the auction is at least in partdetermined using the uCTR of the webpage keyword, and wherein, based onthe result, the webpage keyword is used, instead of the current-webpagekeyword, to evoke the subsequent advertisement, which is served to therecipient-device user.
 9. The method of claim 8, wherein, when theinitial advertisement is evoked by the webpage keyword and the initialadvertisement is not selected by the recipient-device user, the mCTR isrepresented by a first ratio: (SEL/IMP), wherein SEL is a number oftimes an advertisement evoked by the webpage keyword is selected by anyuser of any recipient device when the advertisement is served in theinitial fillable advertisement space, and wherein IMP is a number oftimes the advertisement is served to any recipient device in the initialfillable advertisement space.
 10. The method of claim 9, wherein, whenthe initial advertisement is evoked by the webpage keyword and theinitial advertisement is selected by the recipient-device user, the mCTRis represented by a second ratio: (SEL/CLI), and wherein CLI is a numberof times the advertisement is served to all users that selected theadvertisement.
 11. The method of claim 9, wherein, when the initialadvertisement is not evoked by the webpage keyword, but the webpagekeyword was a source usable to evoke an alternative advertisement, themCTR is calculated using a first formula represented by:mCTR=(SEL/IMP)*(IMP/SOU)^(α), wherein SOU is equal to the number oftimes the webpage keyword was a source to evoke the alternativeadvertisement, regardless of whether the alternative advertisement wasserved, and wherein α is a parameter that is learned.
 12. The method ofclaim 11, wherein, when the initial advertisement is not evoked by thewebpage keyword and the webpage keyword was not a source to evoke thealternative advertisement, the mCTR is calculated using a second formularepresented by: mCTR=((SEL/IMP)*(IMP/SOU)^(α))*(SOU/TOT)^(β), whereinTOT is equal to a number of times the initial fillable advertisementspace was served to any user of any recipient device, and wherein β is aparameter that is learned.
 13. The method of claim 8 further comprising,ranking the webpage keyword as a user keyword among other user keywords,wherein a keyword score of the user keyword is determined using the uCTRand wherein the keyword score is used to rank the user keyword.
 14. Themethod of claim 13, wherein the keyword score comprises a product of theuCTR and a cost-per-click value of serving a given advertisement evokedby the user keyword.
 15. The method of claim 14, wherein the keywordscore comprises the product minus an expected opportunity cost of notserving a contextual advertisement on a given webpage.
 16. The method ofclaim 8, wherein the result is determined by assigning a respectiveauction rank to each of the webpage keyword and the current-webpagekeyword, wherein a first auction rank of the webpage keyword is equal toa product of a first bid and the uCTR, and wherein the first auctionrank is more favorable than a second auction rank of the current-webpagekeyword, such that, based at least in part on the uCTR, the webpagekeyword is used to evoke the subsequent advertisement.
 17. The method ofclaim 16, wherein the second auction rank is equal to a product of asecond bid, a predicted click-through-rate (pCTR), and a measure ofrelevance of the current-webpage keyword to the subsequent webpage, andwherein the pCTR quantifies a general relevance between thecurrent-webpage keyword and a potential advertisement evoked by thecurrent-webpage keyword, the general relevance not taking into account arelevance of the current-webpage keyword to the recipient-device user.18. A system, which is employed using a processor and computer-readablemedia, that selects an advertisement to be displayed on a webpage, thesystem comprising: a user-criteria database storing a user-associatedcriterion together with a user-behavior click-through-rate (uCTR),wherein the user-associated criterion was available to evoke an initialadvertisement that was previously served together with an initialwebpage to a user, and wherein the uCTR suggests whether a subsequentadvertisement served with a subsequent webpage will be selected by theuser when the subsequent advertisement is evoked by the user-associatedcriterion; a criteria-stat generator that calculates the uCTR byapplying a link function to a measured click-through-rate (mCTR), whichquantifies a contextual relevance of the user-associated criterion tothe user in a context of when the initial webpage was served; and acriteria evaluator that conducts an auction between the user-associatedcriterion and a current-webpage criteria, which is included in amongcontent of the subsequent webpage.
 19. The system of claim 18, wherein avalue of the mCTR is dependent on whether the user-associated criterionwas used to evoke the initial advertisement.
 20. The system of claim 19,wherein, when the user-associated criterion was used to evoke theinitial advertisement, the value of the mCTR is dependent on whether theinitial advertisement was selected by the user.